Riley, RD ORCID: 0000-0001-8699-0735 (2016) Explicit inclusion of treatment in prognostic modelling was recommended in observational and randomised settings. Journal of Clinical Epidemiology, 78. pp. 90-100. ISSN 0895-4356

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Abstract

Objectives
To compare different methods to handle treatment when developing a prognostic model that aims to produce accurate probabilities of the outcome of individuals if left untreated.

Study Design and Setting
Simulations were performed based on two normally distributed predictors, a binary outcome, and a binary treatment, mimicking a randomized trial or an observational study. Comparison was made between simply ignoring treatment (SIT), restricting the analytical data set to untreated individuals (AUT), inverse probability weighting (IPW), and explicit modeling of treatment (MT). Methods were compared in terms of predictive performance of the model and the proportion of incorrect treatment decisions.

Results
Omitting a genuine predictor of the outcome from the prognostic model decreased model performance, in both an observational study and a randomized trial. In randomized trials, the proportion of incorrect treatment decisions was smaller when applying AUT or MT, compared to SIT and IPW. In observational studies, MT was superior to all other methods regarding the proportion of incorrect treatment decisions.

Conclusion
If a prognostic model aims to produce correct probabilities of the outcome in the absence of treatment, ignoring treatments that affect that outcome can lead to suboptimal model performance and incorrect treatment decisions. Explicitly, modeling treatment is recommended.

Item Type: Article
Additional Information: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Elsevier at http://dx.doi.org/10.1016/j.jclinepi.2016.03.017 Please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: Prognosis, Models, Statistical, Computer simulation, Decision support techniques, Calibration
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > Primary Care Health Sciences
Depositing User: Symplectic
Date Deposited: 04 Apr 2016 09:41
Last Modified: 13 Aug 2018 10:23
URI: http://eprints.keele.ac.uk/id/eprint/1613

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